Coastal Drone Survey Platform

Our team was responsible for designing and developing the software layer that connects drones, field teams and cloud data into one workflow.

1. Mission Planning & Operator Apps

Fordewind delivered a web-based mission planning portal and companion tools for field operators, built around the needs of repeat surveys:

• Web-planned missions — survey areas, flight routes, altitude and camera settings defined on a map in the browser and saved as reusable mission plans
• Repeat missions — the same flight plan can be re-flown on every visit, so imagery from different dates covers the same area the same way
• Fieldwork assignment — missions assigned to operators and tracked from the office, with a clear view of what’s been flown and what’s still pending
• Companion apps — operator apps that bring the planned mission into the field and report progress back to the web portal

The core idea behind the solution is repeatability. A single survey shows what the shoreline looks like today; a series of identical surveys shows how it’s changing. By treating each mission as a reusable plan rather than a one-off flight, the platform makes every new dataset directly comparable with the last — the foundation for any change analysis, manual or AI-powered.

2. Drone & Sensor Integration

• Connected drone autopilots and device APIs, including DJI SDKs and ArduPilot, to send missions to the aircraft and pull flight data back
• Linked flight telemetry, camera and payload sensor data to each mission, so every image is tied to its location, time and flight
• Built the integration layer around the client’s hardware, leaving room to add new drone models or sensors without rebuilding the platform

3. IoT & Cloud Connectivity

• Implemented upload queues that move imagery from the field to the cloud reliably, even where coastal connectivity is limited
• Built telemetry pipelines that bring device status and flight data into the platform using MQTT, REST APIs and WebSockets
• Set up alerts for mission status and completed uploads, so the office team knows when new data is ready for review
• Used AWS IoT Core for secure, scalable device-to-cloud communication

4. Maps & Spatial Data

• Developed a map-based web interface on OpenLayers for planning missions and reviewing survey results
• Stored survey areas, flight paths and imagery footprints in PostgreSQL / PostGIS
• Used GDAL to process geospatial imagery formats and coordinate systems
• Organized imagery by location and date, so every survey of a coastal section can be reviewed alongside earlier ones

5. Next Phase: Computer Vision & AI

Building on the platform, Fordewind has outlined an AI extension for the client:

• The same approach extends to object detection and image triage in other inspection workflows
• Computer vision models that compare imagery from repeat surveys and flag shoreline changes
• Findings mapped and routed to specialists for review — AI speeds up the search, experts make the final call